A visualization system for intelligent diagnosis and statistical analysis of oral diseases based on panoramic radiography

Panoramic radiography is an essential auxiliary diagnostic tool for oral diseases. It is a difficult and time-consuming task to conduct extensive panoramic radiography interpretation. These challenges are exacerbated by the creation of electronic medical records and the investigation of oral diseases using collective data. So, we develop a visualization system based on panoramic radiographs. Its function focuses on the intelligent diagnosis and statistical analysis of oral diseases. Firstly, we provide a human-machine collaborative tool for the diagnosis and data extraction of oral diseases in panoramic radiographs. After that, the system generates electronic medical records, including visual charts of oral health status and radiology reports. We further develop statistical correlation analysis to visually evaluate and interactively explore the statistical data from oral health surveys. We conduct intelligent diagnosis, obtain the electronic medical records and do collective analysis based on 521 panoramic radiographs. The available analyses cover disease-prone teeth, disease distribution per tooth position and association of age, sex with oral diseases. The results are reported from a comprehensive case study showing that our system can improve the efficiency in disease detection and data mining. It can also fuel research studies in the field of public oral health and provide robust support for oral healthcare strategies.

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Publication Details

Journal
Scientific Reports
Published
2025-05-25
DOI
https://doi.org/10.1038/s41598-025-01733-5
Citations
3
Primary Topic
Dental Radiography and Imaging
Type
article
Field-Weighted Citation Impact
5.37

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article

A visualization system for intelligent diagnosis and statistical analysis of oral diseases based on panoramic radiography

Miaoxin Hu, Zhiguang Zhou, Tianya Pan, Shenji Zhu et al.
3 citations
Scientific Reports
Dental Radiography and Imaging
5.37
article

A visualization system for intelligent diagnosis and statistical analysis of oral diseases based on panoramic radiography

Miaoxin Hu, Zhiguang Zhou, Tianya Pan, Shenji Zhu, Ting Xu, Yue Hong
article en
3 citations

Abstract

Panoramic radiography is an essential auxiliary diagnostic tool for oral diseases. It is a difficult and time-consuming task to conduct extensive panoramic radiography interpretation. These challenges are exacerbated by the creation of electronic medical records and the investigation of oral diseases using collective data. So, we develop a visualization system based on panoramic radiographs. Its function focuses on the intelligent diagnosis and statistical analysis of oral diseases. Firstly, we provide a human-machine collaborative tool for the diagnosis and data extraction of oral diseases in panoramic radiographs. After that, the system generates electronic medical records, including visual charts of oral health status and radiology reports. We further develop statistical correlation analysis to visually evaluate and interactively explore the statistical data from oral health surveys. We conduct intelligent diagnosis, obtain the electronic medical records and do collective analysis based on 521 panoramic radiographs. The available analyses cover disease-prone teeth, disease distribution per tooth position and association of age, sex with oral diseases. The results are reported from a comprehensive case study showing that our system can improve the efficiency in disease detection and data mining. It can also fuel research studies in the field of public oral health and provide robust support for oral healthcare strategies.

Scientific ReportsVol. 15(1)
First Affiliated Hospital Zhejiang University (CN), Hangzhou Dianzi University (CN), Zhejiang University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 5%
Dental Radiography and Imaging
5.37
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A visualization system for intelligent diagnosis and statistical analysis of oral diseases based on panoramic radiography — Miaoxin Hu, Zhiguang Zhou, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS